{"as_of":"2026-08-20T06:00:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f58d26bd299b9d6af17e117ec5aa70bd9ef3a9540c9f580d431396d5946c14b8","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":45,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":45,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":45,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":45,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T11:41:52.912830Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"pith","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":21,"observed_at":"2026-08-05T02:28:24.338817Z","source":"pith"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-10T18:16:25.537683Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.12418","last_updated":"2025-01-20T13:43:45Z","snapshot_observed_at":"2026-08-14T16:41:20.065713Z","submitted_at":"2025-01-20T13:43:45Z","title":"ImageRef-VL: Enabling Contextual Image Referencing in Vision-Language Models","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-10T18:16:25.537683Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2501.12418"},"observation_digest":"sha256:ffe810ff6b857c55172fab53649db8ac97098f320e1f17909eefe08b795c0619","observation_id":"cd25219e-df64-40b9-b348-54153b77cf7f","resolution":{"observed_at":"2026-08-10T18:16:25.537683Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":"2410.12837","doi":"10.48550/arxiv.2410.12837","metadata_source":"pith","pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":"cs.CL","work_id":"493b914c-9bce-4127-8102-59c45c8710f2","year":2024},"citing_paper":{"arxiv_id":"2504.01990","last_updated":"2025-08-02T12:44:02Z","snapshot_observed_at":"2026-08-12T16:45:40.094278Z","submitted_at":"2025-03-31T18:00:29Z","title":"Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems","version":2},"reference_index":150,"source":"pdf_text","source_observed_at":"2026-05-22T21:39:49.832151Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2504.01990"},"observation_digest":"sha256:0961780bd258cbd47eb4c4b280c69edf878d2c26f5a38eeae6339db2c84e780f","observation_id":"f678df7c-245d-4687-a375-2132a752e694","resolution":{"observed_at":"2026-05-22T21:42:10.895596Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-16T11:41:52.912830Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.14917","last_updated":"2025-04-21T07:35:24Z","snapshot_observed_at":"2026-08-18T13:06:18.133674Z","submitted_at":"2025-04-21T07:35:24Z","title":"POLYRAG: Integrating Polyviews into Retrieval-Augmented Generation for Medical Applications","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-16T11:41:52.912830Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2504.14917"},"observation_digest":"sha256:83b361e65747b92b76f75384fd888765a66f271ce1afa39b62597edad3851ef0","observation_id":"07f8a476-a413-4869-afc2-8e7105d9464a","resolution":{"observed_at":"2026-08-16T11:41:52.912830Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-16T05:46:52.732860Z","title":"https://doi.org/10.48550/arXiv.2410.12837","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.19754","last_updated":"2025-04-28T12:52:05Z","snapshot_observed_at":"2026-08-18T02:01:33.867835Z","submitted_at":"2025-04-28T12:52:05Z","title":"Reconstructing Context: Evaluating Advanced Chunking Strategies for Retrieval-Augmented Generation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T05:46:52.732860Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2504.19754"},"observation_digest":"sha256:7e33f1658427fe33a7522ffc81d3c864aacd4b20be197eae545e1e2b0dd0f597","observation_id":"420706ad-2645-4db7-8f09-d58caa73a26a","resolution":{"observed_at":"2026-08-16T05:46:52.732860Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-15T22:47:37.245345Z","title":"Gupta, R","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06399","last_updated":"2025-05-09T19:55:22Z","snapshot_observed_at":"2026-08-18T11:22:22.163501Z","submitted_at":"2025-05-09T19:55:22Z","title":"LLM-Land: Large Language Models for Context-Aware Drone Landing","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-15T22:47:37.245345Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2505.06399"},"observation_digest":"sha256:9d8cf7612326e6537c137f3e11a2e3e45c3f3a143736527eab7c32c4102861a9","observation_id":"b17fa196-057f-4ed3-a57a-203533258290","resolution":{"observed_at":"2026-08-15T22:47:37.245345Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-15T21:00:42.507917Z","title":"CoRR abs/2410.12837(2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.11180","last_updated":"2025-05-16T12:31:29Z","snapshot_observed_at":"2026-08-18T22:58:30.047192Z","submitted_at":"2025-05-16T12:31:29Z","title":"mmRAG: A Modular Benchmark for Retrieval-Augmented Generation over Text, Tables, and Knowledge Graphs","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T21:00:42.507917Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2505.11180"},"observation_digest":"sha256:3daebf7670cdc4ed9f051d296dd0607d255e6c880f407dd8209f578b4bdf635d","observation_id":"4be15e7e-b980-4dbe-b1a6-1e6b7697ac76","resolution":{"observed_at":"2026-08-15T21:00:42.507917Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-15T20:48:22.681977Z","title":"Ranjan, S","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.12065","last_updated":"2025-05-17T16:07:01Z","snapshot_observed_at":"2026-08-19T16:38:48.229330Z","submitted_at":"2025-05-17T16:07:01Z","title":"Demystifying and Enhancing the Efficiency of Large Language Model Based Search Agents","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T20:48:22.681977Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2505.12065"},"observation_digest":"sha256:d3d263a74ba3461a7545a3d12b84fff5e0bb4c250375b0d00d2e78e803dd42f3","observation_id":"cd6188ad-2d3e-4af9-a8c5-0acd8e6090dd","resolution":{"observed_at":"2026-08-15T20:48:22.681977Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-15T20:31:58.966490Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.12731","last_updated":"2025-05-25T13:03:54Z","snapshot_observed_at":"2026-08-19T14:01:18.037272Z","submitted_at":"2025-05-19T05:39:38Z","title":"Accelerating Adaptive Retrieval Augmented Generation via Instruction-Driven Representation Reduction of Retrieval Overlaps","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-15T20:31:58.966490Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2505.12731"},"observation_digest":"sha256:6e172f7a881ed2cf01248dbc8748ebdfb4318b876f043a762deaa33e794cf568","observation_id":"8d87e74a-efc7-427e-b381-e86e8ad180ea","resolution":{"observed_at":"2026-08-15T20:31:58.966490Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-07T14:37:22.521990Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.20320","last_updated":"2025-05-23T16:13:08Z","snapshot_observed_at":"2026-08-14T10:57:34.894237Z","submitted_at":"2025-05-23T16:13:08Z","title":"Less Context, Same Performance: A RAG Framework for Resource-Efficient LLM-Based Clinical NLP","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T14:37:22.521990Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2505.20320"},"observation_digest":"sha256:5d22b255ea760de9acbeef0fb53422d5cb64a00c856e92dc72e9e126fa73229d","observation_id":"29fd5fc0-5c39-498d-a4e1-6d8c0c0989df","resolution":{"observed_at":"2026-08-07T14:37:22.521990Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-07T12:24:16.174083Z","title":"A compre- hensive survey of retrieval-augmented generation (rag): Evolution, cur- rent landscape and future directions","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.24478","last_updated":"2025-05-30T11:27:59Z","snapshot_observed_at":"2026-08-14T13:49:22.074679Z","submitted_at":"2025-05-30T11:27:59Z","title":"Optimizing the Interface Between Knowledge Graphs and LLMs for Complex Reasoning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T12:24:16.174083Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2505.24478"},"observation_digest":"sha256:2c3324bd1d4b45617e4b726efee8c52a18c1c8af6e3cce24600d38edc28bb040","observation_id":"d36934c4-3c63-46c1-92c8-ac7bbe1b127a","resolution":{"observed_at":"2026-08-07T12:24:16.174083Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-07T00:41:41.140198Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13038","last_updated":"2025-06-17T14:31:50Z","snapshot_observed_at":"2026-08-17T22:32:25.926648Z","submitted_at":"2025-06-16T02:03:41Z","title":"HKD4VLM: A Progressive Hybrid Knowledge Distillation Framework for Robust Multimodal Hallucination and Factuality Detection in VLMs","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T00:41:41.140198Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2506.13038"},"observation_digest":"sha256:7171d5bea5659ff1e4ada2ee616f9f94a83e2fa95d8cc818c26c941555d9cc18","observation_id":"9b388208-b4d7-4591-8255-89f5c7340e4f","resolution":{"observed_at":"2026-08-07T00:41:41.140198Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-07T13:59:48.036157Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.15690","last_updated":"2025-07-24T05:08:02Z","snapshot_observed_at":"2026-08-15T18:11:38.661263Z","submitted_at":"2025-05-26T22:10:52Z","title":"LLM Web Dynamics: Tracing Model Collapse in a Network of LLMs","version":3},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-07T13:59:48.036157Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2506.15690"},"observation_digest":"sha256:025885d74870efc7abf92f88e4d2dbb533a20c340404eeae3ad19f52ea70f45f","observation_id":"fd74e12a-d6dc-487e-b885-e5f85a855c71","resolution":{"observed_at":"2026-08-07T13:59:48.036157Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-06T22:42:04.419464Z","title":"https://arxiv.org/abs/2410.12837","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20869","last_updated":"2025-09-24T07:46:21Z","snapshot_observed_at":"2026-08-08T07:48:43.352052Z","submitted_at":"2025-06-25T22:40:00Z","title":"Engineering RAG Systems for Real-World Applications: Design, Development, and Evaluation","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T22:42:04.419464Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2506.20869"},"observation_digest":"sha256:f6ff3d38bc4ecb3f010a3c908f3a87ceeac7375e655372872384e6fc0ec236d4","observation_id":"b8a4e44b-0a44-4ed5-8913-32a6fa8dd718","resolution":{"observed_at":"2026-08-06T22:42:04.419464Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-06T19:43:56.709862Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.04748","last_updated":"2025-07-07T08:19:17Z","snapshot_observed_at":"2026-08-17T02:48:24.509682Z","submitted_at":"2025-07-07T08:19:17Z","title":"LLM-based Question-Answer Framework for Sensor-driven HVAC System Interaction","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:56.709862Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2507.04748"},"observation_digest":"sha256:61ad78c9ca7244559a1b69d97b04748c5b21cde560e8a017dcfbf11e47a905b1","observation_id":"886e72e0-6e73-4f0c-88ad-3057dd7f7ccc","resolution":{"observed_at":"2026-08-06T19:43:56.709862Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-06T18:32:20.431208Z","title":"& Ranjan, R","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.07983","last_updated":"2025-07-10T17:56:03Z","snapshot_observed_at":"2026-08-18T20:33:40.093369Z","submitted_at":"2025-07-10T17:56:03Z","title":"Performance and Practical Considerations of Large and Small Language Models in Clinical Decision Support in Rheumatology","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T18:32:20.431208Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2507.07983"},"observation_digest":"sha256:5c4cbea29c63eb9abd348ca01b615c75637df55b78fefb4770d52e5474f07736","observation_id":"66fb15fc-b1cc-498b-a02e-b849f8e01458","resolution":{"observed_at":"2026-08-06T18:32:20.431208Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-06T18:54:03.131339Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.13369","last_updated":"2025-07-09T17:06:54Z","snapshot_observed_at":"2026-08-17T07:21:35.772213Z","submitted_at":"2025-07-09T17:06:54Z","title":"VerilogDB: The Largest, Highest-Quality Dataset with a Preprocessing Framework for LLM-based RTL Generation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T18:54:03.131339Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2507.13369"},"observation_digest":"sha256:08054a04826c16baa8ab03a0bc2044a55f62eb2caf21950ca480a27abde6e827","observation_id":"78aa2294-6bdd-4293-a63e-52b6df3efae6","resolution":{"observed_at":"2026-08-06T18:54:03.131339Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T22:34:14.423146Z","title":"A comprehensive survey of retrieval-augmented generation (rag): Evolution, current landscape and future directions,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.06888","last_updated":"2025-08-09T08:35:40Z","snapshot_observed_at":"2026-08-18T07:06:34.085056Z","submitted_at":"2025-08-09T08:35:40Z","title":"Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T22:34:14.423146Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2508.06888"},"observation_digest":"sha256:e52f6ce4ded38576385f3eb13e097e8f5c23cf3343d9408d7199d6c24cad17a4","observation_id":"802589a2-8d22-4a93-bd16-f50ed23ee897","resolution":{"observed_at":"2026-08-05T22:34:14.423146Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T16:21:00.440034Z","title":"A comprehensive survey of retrieval-augmented generation (rag): Evolution, current landscape and future directions,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.18725","last_updated":"2025-08-26T06:50:11Z","snapshot_observed_at":"2026-08-20T03:55:31.552070Z","submitted_at":"2025-08-26T06:50:11Z","title":"Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions","version":1},"reference_index":244,"source":"pdf_text","source_observed_at":"2026-08-05T16:21:00.440034Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2508.18725"},"observation_digest":"sha256:2f778052d817334372d2c58ccd8253a03f7d8073f9252118f11bbfdf2bfa30cd","observation_id":"772896c6-f706-402a-83fb-22a3b6d1d174","resolution":{"observed_at":"2026-08-05T16:21:00.440034Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T14:54:06.167889Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.20778","last_updated":"2025-08-31T09:48:40Z","snapshot_observed_at":"2026-08-14T04:38:41.540709Z","submitted_at":"2025-08-28T13:34:42Z","title":"SEAL: Structure and Element Aware Learning to Improve Long Structured Document Retrieval","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-05T14:54:06.167889Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2508.20778"},"observation_digest":"sha256:e92f298bc0fdc69cd3a660e3c2c34d0574aa9354660e1816dca7f31ad03aa865","observation_id":"cf6cb4fe-9fd7-4990-b052-279b1261a425","resolution":{"observed_at":"2026-08-05T14:54:06.167889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T14:28:38.856963Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.21307","last_updated":"2025-08-29T02:08:36Z","snapshot_observed_at":"2026-08-16T20:17:07.617285Z","submitted_at":"2025-08-29T02:08:36Z","title":"MultiFluxAI Enhancing Platform Engineering with Advanced Agent-Orchestrated Retrieval Systems","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T14:28:38.856963Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2508.21307"},"observation_digest":"sha256:053d822497d6e84f1585bbe36ff339e430210281a54ee749bbb6e5498b7f70c8","observation_id":"9fa814c3-ad02-482f-a63b-0aae319500ea","resolution":{"observed_at":"2026-08-05T14:28:38.856963Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T13:36:36.408442Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.00520","last_updated":"2025-08-30T14:56:53Z","snapshot_observed_at":"2026-08-17T11:48:12.745562Z","submitted_at":"2025-08-30T14:56:53Z","title":"ERank: Fusing Supervised Fine-Tuning and Reinforcement Learning for Effective and Efficient Text Reranking","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-05T13:36:36.408442Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2509.00520"},"observation_digest":"sha256:7848a6a5de3aa7ec9edc0709ac9d1112d9b9f07f84e23e3fec76cf8292895732","observation_id":"a7f07315-2810-4684-8c03-4f67cb2fa583","resolution":{"observed_at":"2026-08-05T13:36:36.408442Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-04T21:59:32.410831Z","title":"Acomprehensivesurveyofretrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.07620","last_updated":"2025-09-09T11:47:40Z","snapshot_observed_at":"2026-08-15T07:59:53.510814Z","submitted_at":"2025-09-09T11:47:40Z","title":"Towards End-to-End Model-Agnostic Explanations for RAG Systems","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-04T21:59:32.410831Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2509.07620"},"observation_digest":"sha256:6b02cbcd765af0fa80edf03413a3fb840e8e244362812d4ff79f383b9382a3ec","observation_id":"b90333f1-2f56-4855-ac5d-3f472b6f1b2a","resolution":{"observed_at":"2026-08-04T21:59:32.410831Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":"2410.12837","doi":"10.48550/arxiv.2410.12837","metadata_source":"pith","pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":"cs.CL","work_id":"493b914c-9bce-4127-8102-59c45c8710f2","year":2024},"citing_paper":{"arxiv_id":"2510.02657","last_updated":"2026-01-16T01:29:15Z","snapshot_observed_at":"2026-08-13T07:58:48.811843Z","submitted_at":"2025-10-03T01:26:13Z","title":"Less LLM, More Documents: Searching for Improved RAG","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-18T11:13:01.397197Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2510.02657"},"observation_digest":"sha256:01a90672bb3599706020dd138eedd0a88b1fbd5cf04cef850a92e43ad09c817e","observation_id":"6cc75e68-7d66-46ce-9a2f-413b9141c54b","resolution":{"observed_at":"2026-05-18T11:16:19.244543Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-04T11:23:49.343516Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions.arXiv preprint arXiv:2410.12837,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2510.05363","last_updated":"2026-06-04T21:50:20Z","snapshot_observed_at":"2026-08-10T11:35:22.942093Z","submitted_at":"2025-10-06T20:41:43Z","title":"MHA-RAG: Improving Efficiency, Accuracy, and Consistency by Encoding Exemplars as Soft Prompts","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-04T11:23:49.343516Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2510.05363"},"observation_digest":"sha256:ba3f54711c3606fed166267f7102b1144c2b82b89618330bbf51821fe602a036","observation_id":"8ac32093-e12a-44a4-9f05-5b5350804b55","resolution":{"observed_at":"2026-08-04T11:23:49.343516Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":"2410.12837","doi":"10.48550/arxiv.2410.12837","metadata_source":"pith","pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":"cs.CL","work_id":"493b914c-9bce-4127-8102-59c45c8710f2","year":2024},"citing_paper":{"arxiv_id":"2511.09282","last_updated":"2026-04-11T11:33:33Z","snapshot_observed_at":"2026-08-11T12:41:23.442130Z","submitted_at":"2025-11-12T12:49:30Z","title":"End-to-end Contrastive Language-Speech Pretraining Model For Long-form Spoken Question Answering","version":3},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-05-17T22:44:49.949759Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2511.09282"},"observation_digest":"sha256:1065a19c1a2fb512193b75dd99e171f25e924b2c7d586fe3657a933040268c30","observation_id":"2e79b35b-9d94-47ec-bdce-26e2dfb6ee57","resolution":{"observed_at":"2026-05-17T22:45:24.242812Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-03T15:45:14.281765Z","title":"A comprehensive survey of retrieval-augmented generation (rag): Evolution, current landscape and future directions.arXiv preprint arXiv:2410.12837, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.15922","last_updated":"2026-05-24T16:47:21Z","snapshot_observed_at":"2026-08-15T17:11:58.207187Z","submitted_at":"2025-12-17T19:38:35Z","title":"Leveraging Spreading Activation for Improved Document Retrieval in Knowledge-Graph-Based RAG Systems","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-03T15:45:14.281765Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2512.15922"},"observation_digest":"sha256:e66bab18a940d090df69d4d04a40a72b17e67617e14dca43117048d4634d36b8","observation_id":"8043200b-5af8-495c-af76-e9e0b5eb4f39","resolution":{"observed_at":"2026-08-03T15:45:14.281765Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":"2410.12837","doi":"10.48550/arxiv.2410.12837","metadata_source":"pith","pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":"cs.CL","work_id":"493b914c-9bce-4127-8102-59c45c8710f2","year":2024},"citing_paper":{"arxiv_id":"2603.17418","last_updated":"2026-07-05T09:53:30Z","snapshot_observed_at":"2026-08-15T21:47:31.158855Z","submitted_at":"2026-03-18T06:52:47Z","title":"PowerDAG: Supervisory Agentic AI System for Automating Distribution Grid Analysis","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-15T09:29:11.147253Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2603.17418"},"observation_digest":"sha256:bf99123848e3d499c43c25b3569f50a061a34d50b74e40d8fe04df2537ecec05","observation_id":"eb6db02c-7790-497a-abd0-ffe1601b5777","resolution":{"observed_at":"2026-05-15T09:29:53.411321Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-07-13T23:12:55.091668Z","title":"A comprehensive survey of retrieval-augmented generation (rag): Evolution, current landscape and future directions,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2603.17418","last_updated":"2026-07-05T09:53:30Z","snapshot_observed_at":"2026-08-15T21:47:31.158855Z","submitted_at":"2026-03-18T06:52:47Z","title":"PowerDAG: Supervisory Agentic AI System for Automating Distribution Grid Analysis","version":4},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-13T23:12:55.091668Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2603.17418"},"observation_digest":"sha256:75220b6ecfe04fe05a31312f268dc262444e8ee07f859466b802c4ac0b841424","observation_id":"8bec26e2-5057-4b74-a27c-bb01b4e2a06c","resolution":{"observed_at":"2026-07-13T23:12:55.091668Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":"2410.12837","doi":"10.48550/arxiv.2410.12837","metadata_source":"pith","pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":"cs.CL","work_id":"493b914c-9bce-4127-8102-59c45c8710f2","year":2024},"citing_paper":{"arxiv_id":"2604.14222","last_updated":"2026-04-14T10:48:13Z","snapshot_observed_at":"2026-08-11T13:36:08.885103Z","submitted_at":"2026-04-14T10:48:13Z","title":"Adaptive Query Routing: A Tier-Based Framework for Hybrid Retrieval Across Financial, Legal, and Medical Documents","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-10T14:42:00.856705Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2604.14222"},"observation_digest":"sha256:7ef960ed80343f92d653bf845ca89f94bdb44e2ef6a1e465784455ef55394212","observation_id":"dc574114-772e-4118-9bbd-5d58b25fd4e4","resolution":{"observed_at":"2026-05-10T14:45:40.554796Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":"2410.12837","doi":"10.48550/arxiv.2410.12837","metadata_source":"pith","pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":"cs.CL","work_id":"493b914c-9bce-4127-8102-59c45c8710f2","year":2024},"citing_paper":{"arxiv_id":"2604.16316","last_updated":"2026-02-08T22:30:27Z","snapshot_observed_at":"2026-08-13T12:04:52.578395Z","submitted_at":"2026-02-08T22:30:27Z","title":"CrossTraffic: An Open-Source Framework for Reproducible and Executable Transportation Analysis and Knowledge Management","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-16T05:44:47.946128Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2604.16316"},"observation_digest":"sha256:1d4f319411bb601942906eed009e09b09dc74ae1f3e9e2aa8f2fa3e7ce578731","observation_id":"43a8c41f-1e53-494c-89bf-b4e1065407e0","resolution":{"observed_at":"2026-05-16T05:47:23.984697Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":"2410.12837","doi":"10.48550/arxiv.2410.12837","metadata_source":"pith","pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":"cs.CL","work_id":"493b914c-9bce-4127-8102-59c45c8710f2","year":2024},"citing_paper":{"arxiv_id":"2604.17843","last_updated":"2026-04-20T05:53:52Z","snapshot_observed_at":"2026-08-04T13:05:53.222299Z","submitted_at":"2026-04-20T05:53:52Z","title":"Learning from AVA: Early Lessons from a Curated and Trustworthy Generative AI for Policy and Development Research","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-10T04:38:00.482850Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2604.17843"},"observation_digest":"sha256:82549f15005ad1fa123a3ebe5ef2e6778ba97bf039aa161ef733e2695fffe655","observation_id":"4c04bc8c-7294-4879-9f6c-2984e678999a","resolution":{"observed_at":"2026-05-10T12:10:22.870516Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":"2410.12837","doi":"10.48550/arxiv.2410.12837","metadata_source":"pith","pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":"cs.CL","work_id":"493b914c-9bce-4127-8102-59c45c8710f2","year":2024},"citing_paper":{"arxiv_id":"2604.21679","last_updated":"2026-04-23T13:43:28Z","snapshot_observed_at":"2026-08-11T19:31:26.627191Z","submitted_at":"2026-04-23T13:43:28Z","title":"A Sociotechnical, Practitioner-Centered Approach to Technology Adoption in Cybersecurity Operations: An LLM Case","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-09T21:41:43.874283Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2604.21679"},"observation_digest":"sha256:7ed55af957f374e2e8009559ae3d0eb32641ff9c40599a392940db0ad84c75be","observation_id":"06b0a76b-f44f-42e0-a538-447e707b3cc5","resolution":{"observed_at":"2026-05-11T14:31:06.389277Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":"2410.12837","doi":"10.48550/arxiv.2410.12837","metadata_source":"pith","pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":"cs.CL","work_id":"493b914c-9bce-4127-8102-59c45c8710f2","year":2024},"citing_paper":{"arxiv_id":"2605.00060","last_updated":"2026-04-30T03:19:39Z","snapshot_observed_at":"2026-08-15T17:49:30.098766Z","submitted_at":"2026-04-30T03:19:39Z","title":"TADI: Tool-Augmented Drilling Intelligence via Agentic LLM Orchestration over Heterogeneous Wellsite Data","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-09T21:01:04.815722Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2605.00060"},"observation_digest":"sha256:57e78dbc0fee1d5bf0755b73d941afca04046cc4a0fa5fd90b064ac326dcdc7e","observation_id":"7b535561-5146-47d9-a815-3074f8d68678","resolution":{"observed_at":"2026-05-11T14:51:04.491349Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":"2410.12837","doi":"10.48550/arxiv.2410.12837","metadata_source":"pith","pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":"cs.CL","work_id":"493b914c-9bce-4127-8102-59c45c8710f2","year":2024},"citing_paper":{"arxiv_id":"2605.00943","last_updated":"2026-05-01T07:11:58Z","snapshot_observed_at":"2026-08-11T08:31:36.256032Z","submitted_at":"2026-05-01T07:11:58Z","title":"ARIS: Agentic and Relationship Intelligence System for Social Robots","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-09T19:24:45.954058Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2605.00943"},"observation_digest":"sha256:5eca37d1322f9e33c3bbfd183c040ad4d8647583185ec70d7c60b444a334f01e","observation_id":"1303935f-a585-42a2-865a-18da21e7258f","resolution":{"observed_at":"2026-05-11T15:41:59.635572Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":"2410.12837","doi":"10.48550/arxiv.2410.12837","metadata_source":"pith","pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":"cs.CL","work_id":"493b914c-9bce-4127-8102-59c45c8710f2","year":2024},"citing_paper":{"arxiv_id":"2605.14192","last_updated":"2026-05-13T23:18:07Z","snapshot_observed_at":"2026-08-15T02:53:20.813402Z","submitted_at":"2026-05-13T23:18:07Z","title":"Why Retrieval-Augmented Generation Fails: A Graph Perspective","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-15T04:47:44.904830Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2605.14192"},"observation_digest":"sha256:f9ef0ed7e8b7d21dc735e4c31fb6cafabfc39cf1f00f10b415a39d9d2a3cbd03","observation_id":"78896a1f-40a1-4de6-b844-082afd9dbc99","resolution":{"observed_at":"2026-05-15T04:49:44.254395Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":"2410.12837","doi":"10.48550/arxiv.2410.12837","metadata_source":"pith","pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":"cs.CL","work_id":"493b914c-9bce-4127-8102-59c45c8710f2","year":2024},"citing_paper":{"arxiv_id":"2605.18760","last_updated":"2026-04-06T22:38:15Z","snapshot_observed_at":"2026-07-06T23:29:33.702647Z","submitted_at":"2026-04-06T22:38:15Z","title":"DOTRAG: Retrieval-Time Reasoning Along Paths","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-21T09:11:43.179956Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2605.18760"},"observation_digest":"sha256:6472989ad960c0d0d94f5eb48c084151af7f9858bcb0e2d660ec2f69384b14fb","observation_id":"e41f39db-599e-4e0f-9f14-d295058a1599","resolution":{"observed_at":"2026-05-21T09:14:05.833392Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":"2410.12837","doi":"10.48550/arxiv.2410.12837","metadata_source":"pith","pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":"cs.CL","work_id":"493b914c-9bce-4127-8102-59c45c8710f2","year":2024},"citing_paper":{"arxiv_id":"2606.20173","last_updated":"2026-06-18T12:40:43Z","snapshot_observed_at":"2026-08-16T09:41:41.677616Z","submitted_at":"2026-06-18T12:40:43Z","title":"Qiskit Code Migration with LLMs","version":1},"reference_index":99,"source":"arxiv_source","source_observed_at":"2026-06-26T16:24:25.357338Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2606.20173"},"observation_digest":"sha256:67fc18651e63eb2d2bc18fd484e900152a7639413bed66df4ddb5c2d7b34cabd","observation_id":"8e188fd5-1bf2-49ff-a971-e8e44e7045e3","resolution":{"observed_at":"2026-06-26T16:29:35.732143Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":"2410.12837","doi":"10.48550/arxiv.2410.12837","metadata_source":"pith","pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":"cs.CL","work_id":"493b914c-9bce-4127-8102-59c45c8710f2","year":2024},"citing_paper":{"arxiv_id":"2606.28349","last_updated":"2026-06-03T07:15:11Z","snapshot_observed_at":"2026-08-18T16:03:52.014313Z","submitted_at":"2026-06-03T07:15:11Z","title":"HMARS: A Hierarchical Multi-Agent Memory System for Long-Context Reasoning","version":1},"reference_index":81,"source":"arxiv_source","source_observed_at":"2026-06-30T11:30:52.871762Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2606.28349"},"observation_digest":"sha256:10e1f3009f279a7e2733a0f22fd65a1cc8573525c4dbdc29485fc724b1693bee","observation_id":"96e01ad1-05fb-4f46-8546-f469bc293d3f","resolution":{"observed_at":"2026-06-30T11:34:37.937247Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":"2410.12837","doi":"10.48550/arxiv.2410.12837","metadata_source":"pith","pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":"cs.CL","work_id":"493b914c-9bce-4127-8102-59c45c8710f2","year":2024},"citing_paper":{"arxiv_id":"2607.00013","last_updated":"2026-05-08T12:53:53Z","snapshot_observed_at":"2026-08-02T18:54:27.686892Z","submitted_at":"2026-05-08T12:53:53Z","title":"GRACE-RAG: Governed Retrieval Architecture for Canonical Evidence Synthesis, Enabling Lightweight Deployment in Closed-Domain Institutional Settings","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-07-02T23:39:38.026002Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2607.00013"},"observation_digest":"sha256:c18251bb06501d2336ea237a6c9b80e7eff440b0d6ac37c23378b6f5763657b3","observation_id":"46e7a5ff-2008-435e-b6b1-8dd56dfadca5","resolution":{"observed_at":"2026-07-02T23:47:27.249346Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-07-11T06:35:35.951554Z","title":"A comprehensive survey of retrieval-augmented generation (rag): Evolution, current landscape and future directions","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.05511","last_updated":"2026-07-06T18:00:06Z","snapshot_observed_at":"2026-08-17T20:20:46.823082Z","submitted_at":"2026-07-06T18:00:06Z","title":"Light-Omni: Reflex over Reasoning in Agentic Video Understanding with Long-Term Memory","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-11T06:35:35.951554Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2607.05511"},"observation_digest":"sha256:afd75c6381e62739e296df95e6002fa58c804bfcd6c59b470abd6d2d9be1072b","observation_id":"265d03eb-5414-402a-8d5a-4a3069fc9c00","resolution":{"observed_at":"2026-07-11T06:35:35.951554Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":"2410.12837","doi":"10.48550/arxiv.2410.12837","metadata_source":"pith","pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A comprehensive survey of retrieval- augmented generation (rag): Evolution, current landscape and future directions","venue":"cs.CL","work_id":"493b914c-9bce-4127-8102-59c45c8710f2","year":2024},"citing_paper":{"arxiv_id":"2607.07858","last_updated":"2026-07-08T18:43:34Z","snapshot_observed_at":"2026-08-19T19:18:35.698981Z","submitted_at":"2026-07-08T18:43:34Z","title":"Agentic AI and Retrieval-Augmented Models in Straight-Through Underwriting","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-07-10T16:34:36.568244Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2607.07858"},"observation_digest":"sha256:d1d89b6219387ff02fb7464190af30c13c268e42819ab16c5195f60554f692c4","observation_id":"b9991fee-7145-4a81-9a6e-2e539f233aed","resolution":{"observed_at":"2026-07-10T16:37:23.023458Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-01T10:29:16.256935Z","title":"arXiv preprint arXiv:2410.12837 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.20230","last_updated":"2026-07-22T14:49:10Z","snapshot_observed_at":"2026-08-16T23:59:15.387876Z","submitted_at":"2026-07-22T14:49:10Z","title":"PIER: Physics-Informed Environmental Retrieval for Time-Series Modeling","version":1},"reference_index":83,"source":"arxiv_source","source_observed_at":"2026-08-01T10:29:16.256935Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2607.20230"},"observation_digest":"sha256:091fc5509a4dbc2973e68744dfd9d508dd5ad3cbf7ab2af5da97d679a287b889","observation_id":"6855a3b4-d5b4-46b9-85b4-6bf507ff19f0","resolution":{"observed_at":"2026-08-01T10:29:16.256935Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-02T11:36:04.933133Z","title":"A comprehensive survey ofretrieval-augmentedgeneration(rag):Evolution,currentlandscape and future directions","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:04.933133Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:3cb1ebb12b4fc8a1657e9d412a9be963c35bf8e679310e13966343c0aed59efb","observation_id":"45b6de1c-7bdf-4dbb-83a0-df8f15360e36","resolution":{"observed_at":"2026-08-02T11:36:04.933133Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-03T07:44:26.955121Z","title":"A comprehensive survey of retrieval-augmented gener- ation: Evolution, current landscape and future directions,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29402","last_updated":"2026-07-31T13:22:11Z","snapshot_observed_at":"2026-08-18T18:02:17.405614Z","submitted_at":"2026-07-31T13:22:11Z","title":"Bridging the Question-Answer Gap in Retrieval-Augmented Generation: Hypothetical Prompt Embeddings","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T07:44:26.955121Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2607.29402"},"observation_digest":"sha256:83d2b730e70d93117215bb34e03544fbff4c319dc05cf9d7da89de6bd40876a8","observation_id":"faedcf43-4a07-485b-8a28-b785f099b6a8","resolution":{"observed_at":"2026-08-03T07:44:26.955121Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-14T04:18:12.072442Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.10186","last_updated":"2026-08-10T19:57:19Z","snapshot_observed_at":"2026-08-17T06:12:40.658364Z","submitted_at":"2026-08-10T19:57:19Z","title":"The Deliberative Deficit: An Empirical Critique of LLMs in Democratic Discourse","version":1},"reference_index":249,"source":"arxiv_source","source_observed_at":"2026-08-14T04:18:12.072442Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2608.10186"},"observation_digest":"sha256:b07ff9118d713e2e52d78029323b3fa31589442a9960c6d2290e546233f72c03","observation_id":"7578cdf9-a571-45b8-aa86-9b328798d03d","resolution":{"observed_at":"2026-08-14T04:18:12.072442Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2410.12837/citation-record","integrity":"/paper/2410.12837/integrity","json":"/paper/2410.12837/citation-record.json","paper":"/paper/2410.12837"},"outbound":[],"paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-19T00:54:55.832948Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 45 inbound Pith citation observations for arXiv:2410.12837."}